Hydration of ternary blended cements integrating Drinking Water Treatment Sludge as an artificial pozzolanic material
Bibliographic record
Abstract
One of the biggest challenges facing the cement industry is lowering clinker production without impacting product quality, requiring the investigation of sustainable supplementary cementitious materials (SCMs) in ternary cement system with clinker and limestone. The sludge was thermally treated for 2 h (120 min) at 500°C, 600°C, 700°C, 800°C and 900°C and its reactivity was assessed using R3 protocol through bound water and isothermal calorimetry. Hydration behavior, heat evolution, strength development, and microstructural characteristics were also investigated. Bound water reached its maximum at 600 °C (19.02 %), but this did not enhance strength because hydration was dominated by aluminum-based products rather than calcium silicate hydrate. The optimum activation occurred at 800 °C, where heat release peaked at 211.7 J/g after 7 days and structural changes generated a reactive amorphous phase. Mortars containing 30 % sludge calcined at 800 °C achieved compressive strengths of 47 MPa at 7 days and 65.47 MPa at 28 days. Hydration analysis confirmed the formation of ettringite, monosulfate, and portlandite, highlighting the role of alumino-silicates in strength development. • DWTS evaluated as a sustainable SCM in ternary cement systems. • Optimal calcination temperature of 800°C enhances pozzolanic reactivity. • DWTS-ternary blends achieved 65.47 MPa compressive strength at 28 days. • Hydration products characterized via combined XRD-TGA analysis. • DWTS enables eco-friendly, high-performance cement for carbon neutrality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".